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--- |
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license: apache-2.0 |
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base_model: google/vit-base-patch16-224 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- imagefolder |
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metrics: |
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- accuracy |
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model-index: |
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- name: vit-base-patch16-224-ethosrealdata |
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results: |
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- task: |
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name: Image Classification |
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type: image-classification |
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dataset: |
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name: imagefolder |
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type: imagefolder |
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config: default |
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split: train |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.934010152284264 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# vit-base-patch16-224-ethosrealdata |
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This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2117 |
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- Accuracy: 0.9340 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0002 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:------:|:----:|:---------------:|:--------:| |
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| 0.9707 | 0.9913 | 57 | 0.6825 | 0.8160 | |
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| 0.3507 | 2.0 | 115 | 0.3680 | 0.8909 | |
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| 0.2002 | 2.9913 | 172 | 0.3121 | 0.9023 | |
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| 0.1249 | 4.0 | 230 | 0.2951 | 0.9150 | |
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| 0.1002 | 4.9913 | 287 | 0.2596 | 0.9251 | |
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| 0.1014 | 6.0 | 345 | 0.2615 | 0.9251 | |
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| 0.1261 | 6.9913 | 402 | 0.2437 | 0.9365 | |
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| 0.0556 | 8.0 | 460 | 0.2198 | 0.9416 | |
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| 0.0415 | 8.9913 | 517 | 0.2119 | 0.9416 | |
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| 0.0294 | 9.9130 | 570 | 0.2117 | 0.9340 | |
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### Framework versions |
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- Transformers 4.40.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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